A digital image is a representation of a two-dimensional analog image as a finite set of pixels. Digital images can be created by a variety of devices, such as digital cameras, scanners, and various other computing devices. Digital image processing is the use of computer algorithms to perform image processing on digital images. Image processing operations include, for example, demosaicking, color to grayscale conversion, color adjustment, intensity adjustment, scene analysis, object recognition, white balancing and others.
White balancing refers to the process of adjusting the color in a digital image in order to compensate for color shifts due to scene illumination. White balancing solutions are needed because depending on the illumination or light source of a scene captured in a digital image, color in the captured image can be shifted from the perceived color in the scene. When performed properly, white balancing can be used to produce a visually pleasing white-balanced variant of a digital image.
One problem with many conventional white balancing applications and algorithms is that they are often very computationally intensive. As such, such applications might require the use of relatively expensive computational resources to execute efficiently, which can be prohibitively expensive. In addition, such applications can be very time-consuming to execute—a problem which is exacerbated depending on the computing resources used. Further, such applications can be very difficult to design and implement. Thus, an image processing application/algorithm that could be implemented and executed in a more efficient manner, and in a manner that requires less computational resources, would greatly increase the application's practical value.